Triple

T20390580
Position Surface form Disambiguated ID Type / Status
Subject Narrow Margin E498072 entity
Predicate productionCompany P490 FINISHED
Object Carolco Pictures NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Carolco Pictures | Statement: [Narrow Margin, productionCompany, Carolco Pictures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carolco Pictures
Context triple: [Narrow Margin, productionCompany, Carolco Pictures]
  • A. Carolco Pictures chosen
    Carolco Pictures was an American independent film production company best known for big-budget action movies in the 1980s and early 1990s, including the Rambo and Terminator franchises.
  • B. Cinergi Pictures
    Cinergi Pictures was an independent American film production company active in the 1990s, known for producing big-budget Hollywood films across various genres.
  • C. Konrad Pictures
    Konrad Pictures is a film production company known for working on the romantic fantasy movie "Kate & Leopold."
  • D. Tri-Star Pictures
    Tri-Star Pictures is an American film production and distribution company known for releasing a wide range of Hollywood movies since the 1980s.
  • E. Trimark Pictures
    Trimark Pictures was an American independent film production and distribution company known for releasing low- to mid-budget genre films, including horror and science fiction titles, during the late 1980s and 1990s.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e0b4a71ebc8190b153a36c738730f4 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6790f8d9c819093038f6bb6f47a92 completed April 20, 2026, 7:05 p.m.
Created at: April 16, 2026, 11:28 a.m.